## Fix Python – How do I initialize weights in PyTorch?

How do I initialize weights and biases of a network (via e.g. He or Xavier initialization)?

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How do I initialize weights and biases of a network (via e.g. He or Xavier initialization)?

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How do I save a trained Naive Bayes classifier to disk and use it to predict data?

I have the following sample program from the scikit-learn website:

from sklearn import datasets

iris = datasets.load_iris()

from sklearn.naive_bayes import GaussianNB

gnb = GaussianNB()

y_pred = gnb.fit(iris.data, iris.target).predict(iris.data)

print “Number of mis….

From the Udacity’s deep learning class, the softmax of y_i is simply the exponential divided by the sum of exponential of the whole Y vector:

Where S(y_i) is the softmax function of y_i and e is the exponential and j is the no. of columns in the input vector Y.

I’ve tried the following:

import numpy as np

def softmax(x):

“””Compute softmax v….

Given a 1D array of indices:

a = array([1, 0, 3])

I want to one-hot encode this as a 2D array:

b = array([[0,1,0,0], [1,0,0,0], [0,0,0,1]])

….

In the tensorflow API docs they use a keyword called logits. What is it? A lot of methods are written like:

tf.nn.softmax(logits, name=None)

If logits is just a generic Tensor input, why is it named logits?

Secondly, what is the difference between the following two methods?

tf.nn.softmax(logits, name=None)

tf.nn.softmax_cross_entropy_with_logits….